ui: node editor misc 2 (#4306)

## What type of PR is this? (check all applicable)

- [ ] Refactor
- [x] Feature
- [ ] Bug Fix
- [ ] Optimization
- [ ] Documentation Update
- [ ] Community Node Submission

## Description

Next batch of Node Editor changes.

Author: hipsterusername

.gitignore

@@ -1,23 +1,8 @@
-# ignore default image save location and model symbolic link
 .idea/
-embeddings/
-outputs/
-models/ldm/stable-diffusion-v1/model.ckpt
-**/restoration/codeformer/weights
-
-# ignore user models config
-configs/models.user.yaml
-config/models.user.yml
-invokeai.init
-.version
-.last_model
 
 # ignore the Anaconda/Miniconda installer used while building Docker image
 anaconda.sh
 
-# ignore a directory which serves as a place for initial images
-inputs/
-
 # Byte-compiled / optimized / DLL files
 __pycache__/
 *.py[cod]
@@ -189,39 +174,17 @@ cython_debug/
 #  option (not recommended) you can uncomment the following to ignore the entire idea folder.
 #.idea/
 
-src
 **/__pycache__/
-outputs
 
-# Logs and associated folders
-# created from generated embeddings.
-logs
-testtube
-checkpoints
 # If it's a Mac
 .DS_Store
 
-invokeai/frontend/yarn.lock
-invokeai/frontend/node_modules
-
 # Let the frontend manage its own gitignore
 !invokeai/frontend/web/*
 
 # Scratch folder
 .scratch/
 .vscode/
-gfpgan/
-models/ldm/stable-diffusion-v1/*.sha256
-
-
-# GFPGAN model files
-gfpgan/
-
-# config file (will be created by installer)
-configs/models.yaml
-
-# ignore initfile
-.invokeai
 
 # ignore environment.yml and requirements.txt
 # these are links to the real files in environments-and-requirements

invokeai/app/api_app.py

@@ -122,6 +122,7 @@ def custom_openapi():
 
     output_schemas = schema(output_types, ref_prefix="#/components/schemas/")
     for schema_key, output_schema in output_schemas["definitions"].items():
+        output_schema["class"] = "output"
         openapi_schema["components"]["schemas"][schema_key] = output_schema
 
         # TODO: note that we assume the schema_key here is the TYPE.__name__
@@ -130,8 +131,8 @@ def custom_openapi():
 
     # Add Node Editor UI helper schemas
     ui_config_schemas = schema([UIConfigBase, _InputField, _OutputField], ref_prefix="#/components/schemas/")
-    for schema_key, output_schema in ui_config_schemas["definitions"].items():
-        openapi_schema["components"]["schemas"][schema_key] = output_schema
+    for schema_key, ui_config_schema in ui_config_schemas["definitions"].items():
+        openapi_schema["components"]["schemas"][schema_key] = ui_config_schema
 
     # Add a reference to the output type to additionalProperties of the invoker schema
     for invoker in all_invocations:
@@ -140,8 +141,8 @@ def custom_openapi():
         output_type_title = output_type_titles[output_type.__name__]
         invoker_schema = openapi_schema["components"]["schemas"][invoker_name]
         outputs_ref = {"$ref": f"#/components/schemas/{output_type_title}"}
-
         invoker_schema["output"] = outputs_ref
+        invoker_schema["class"] = "invocation"
 
     from invokeai.backend.model_management.models import get_model_config_enums
 

invokeai/app/invocations/baseinvocation.py

@@ -143,6 +143,7 @@ class UIType(str, Enum):
     # region Misc
     FilePath = "FilePath"
     Enum = "enum"
+    Scheduler = "Scheduler"
     # endregion
 
 
@@ -392,6 +393,13 @@ def get_all_subclasses_tuple(cls):
             toprocess.extend(next_subclasses)
         return tuple(subclasses)
 
+    class Config:
+        @staticmethod
+        def schema_extra(schema: dict[str, Any], model_class: Type[BaseModel]) -> None:
+            if "required" not in schema or not isinstance(schema["required"], list):
+                schema["required"] = list()
+            schema["required"].extend(["type"])
+
 
 class RequiredConnectionException(Exception):
     """Raised when an field which requires a connection did not receive a value."""
@@ -452,6 +460,9 @@ def schema_extra(schema: dict[str, Any], model_class: Type[BaseModel]) -> None:
                 schema["title"] = uiconfig.title
             if uiconfig and hasattr(uiconfig, "tags"):
                 schema["tags"] = uiconfig.tags
+            if "required" not in schema or not isinstance(schema["required"], list):
+                schema["required"] = list()
+            schema["required"].extend(["type", "id"])
 
     @abstractmethod
     def invoke(self, context: InvocationContext) -> BaseInvocationOutput:

invokeai/app/invocations/latent.py

@@ -115,12 +115,14 @@ class DenoiseLatentsInvocation(BaseInvocation):
     noise: Optional[LatentsField] = InputField(description=FieldDescriptions.noise, input=Input.Connection)
     steps: int = InputField(default=10, gt=0, description=FieldDescriptions.steps)
     cfg_scale: Union[float, List[float]] = InputField(
-        default=7.5, ge=1, description=FieldDescriptions.cfg_scale, ui_type=UIType.Float
+        default=7.5, ge=1, description=FieldDescriptions.cfg_scale, ui_type=UIType.Float, title="CFG Scale"
     )
     denoising_start: float = InputField(default=0.0, ge=0, le=1, description=FieldDescriptions.denoising_start)
     denoising_end: float = InputField(default=1.0, ge=0, le=1, description=FieldDescriptions.denoising_end)
-    scheduler: SAMPLER_NAME_VALUES = InputField(default="euler", description=FieldDescriptions.scheduler)
-    unet: UNetField = InputField(description=FieldDescriptions.unet, input=Input.Connection)
+    scheduler: SAMPLER_NAME_VALUES = InputField(
+        default="euler", description=FieldDescriptions.scheduler, ui_type=UIType.Scheduler
+    )
+    unet: UNetField = InputField(description=FieldDescriptions.unet, input=Input.Connection, title="UNet")
     control: Union[ControlField, list[ControlField]] = InputField(
         default=None, description=FieldDescriptions.control, input=Input.Connection
     )
@@ -454,7 +456,7 @@ def _lora_loader():
 
 
 @title("Latents to Image")
-@tags("latents", "image", "vae")
+@tags("latents", "image", "vae", "l2i")
 class LatentsToImageInvocation(BaseInvocation):
     """Generates an image from latents."""
 
@@ -642,7 +644,7 @@ def invoke(self, context: InvocationContext) -> LatentsOutput:
 
 
 @title("Image to Latents")
-@tags("latents", "image", "vae")
+@tags("latents", "image", "vae", "i2l")
 class ImageToLatentsInvocation(BaseInvocation):
     """Encodes an image into latents."""
 

invokeai/app/invocations/math.py

@@ -21,7 +21,7 @@ class AddInvocation(BaseInvocation):
     b: int = InputField(default=0, description=FieldDescriptions.num_2)
 
     def invoke(self, context: InvocationContext) -> IntegerOutput:
-        return IntegerOutput(a=self.a + self.b)
+        return IntegerOutput(value=self.a + self.b)
 
 
 @title("Subtract Integers")
@@ -36,7 +36,7 @@ class SubtractInvocation(BaseInvocation):
     b: int = InputField(default=0, description=FieldDescriptions.num_2)
 
     def invoke(self, context: InvocationContext) -> IntegerOutput:
-        return IntegerOutput(a=self.a - self.b)
+        return IntegerOutput(value=self.a - self.b)
 
 
 @title("Multiply Integers")
@@ -51,7 +51,7 @@ class MultiplyInvocation(BaseInvocation):
     b: int = InputField(default=0, description=FieldDescriptions.num_2)
 
     def invoke(self, context: InvocationContext) -> IntegerOutput:
-        return IntegerOutput(a=self.a * self.b)
+        return IntegerOutput(value=self.a * self.b)
 
 
 @title("Divide Integers")
@@ -66,7 +66,7 @@ class DivideInvocation(BaseInvocation):
     b: int = InputField(default=0, description=FieldDescriptions.num_2)
 
     def invoke(self, context: InvocationContext) -> IntegerOutput:
-        return IntegerOutput(a=int(self.a / self.b))
+        return IntegerOutput(value=int(self.a / self.b))
 
 
 @title("Random Integer")
@@ -81,4 +81,4 @@ class RandomIntInvocation(BaseInvocation):
     high: int = InputField(default=np.iinfo(np.int32).max, description="The exclusive high value")
 
     def invoke(self, context: InvocationContext) -> IntegerOutput:
-        return IntegerOutput(a=np.random.randint(self.low, self.high))
+        return IntegerOutput(value=np.random.randint(self.low, self.high))

invokeai/app/invocations/model.py

@@ -72,7 +72,7 @@ class LoRAModelField(BaseModel):
     base_model: BaseModelType = Field(description="Base model")
 
 
-@title("Main Model Loader")
+@title("Main Model")
 @tags("model")
 class MainModelLoaderInvocation(BaseInvocation):
     """Loads a main model, outputting its submodels."""
@@ -179,7 +179,7 @@ class LoraLoaderOutput(BaseInvocationOutput):
     # fmt: on
 
 
-@title("LoRA Loader")
+@title("LoRA")
 @tags("lora", "model")
 class LoraLoaderInvocation(BaseInvocation):
     """Apply selected lora to unet and text_encoder."""
@@ -257,7 +257,7 @@ class SDXLLoraLoaderOutput(BaseInvocationOutput):
     # fmt: on
 
 
-@title("SDXL LoRA Loader")
+@title("SDXL LoRA")
 @tags("sdxl", "lora", "model")
 class SDXLLoraLoaderInvocation(BaseInvocation):
     """Apply selected lora to unet and text_encoder."""
@@ -356,7 +356,7 @@ class VaeLoaderOutput(BaseInvocationOutput):
     vae: VaeField = OutputField(description=FieldDescriptions.vae, title="VAE")
 
 
-@title("VAE Loader")
+@title("VAE")
 @tags("vae", "model")
 class VaeLoaderInvocation(BaseInvocation):
     """Loads a VAE model, outputting a VaeLoaderOutput"""

invokeai/app/invocations/onnx.py

@@ -169,7 +169,7 @@ class ONNXTextToLatentsInvocation(BaseInvocation):
         ui_type=UIType.Float,
     )
     scheduler: SAMPLER_NAME_VALUES = InputField(
-        default="euler", description=FieldDescriptions.scheduler, input=Input.Direct
+        default="euler", description=FieldDescriptions.scheduler, input=Input.Direct, ui_type=UIType.Scheduler
     )
     precision: PRECISION_VALUES = InputField(default="tensor(float16)", description=FieldDescriptions.precision)
     unet: UNetField = InputField(
@@ -406,7 +406,7 @@ class OnnxModelField(BaseModel):
     model_type: ModelType = Field(description="Model Type")
 
 
-@title("ONNX Model Loader")
+@title("ONNX Main Model")
 @tags("onnx", "model")
 class OnnxModelLoaderInvocation(BaseInvocation):
     """Loads a main model, outputting its submodels."""